Presentation + Paper
15 February 2021 An automated framework for image classification and segmentation of fetal ultrasound images for gestational age estimation
Juan C. Prieto, Hina Shah, Alan J. Rosenbaum, Xiaoning Jiang, Patrick Musonda, Joan T. Price, Elizabeth M. Stringer, Bellington Vwalika, David M. Stamilio, Jeffrey S. A. Stringer
Author Affiliations +
Abstract
Accurate assessment of fetal gestational age (GA) is critical to the clinical management of pregnancy. Industrialized countries rely upon obstetric ultrasound (US) to make this estimate. In low- and middle- income countries, automatic measurement of fetal structures using a low-cost obstetric US may assist in establishing GA without the need for skilled sonographers. We present a technique for generating raw images suitable for model training by removing caliper and text annotation and describe a fully automated pipeline for image classification, segmentation, and structure measurement to estimate the GA. he resulting framework achieves an average accuracy of 93% in classification tasks, a mean Intersection over Union accuracy of 0.91 during segmentation tasks, and a mean measurement error of 1.89 centimeters, finally leading to a 1.4 day mean average error in the predicted GA compared to expert sonographer GA estimate using the Hadlock equation.
Conference Presentation
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juan C. Prieto, Hina Shah, Alan J. Rosenbaum, Xiaoning Jiang, Patrick Musonda, Joan T. Price, Elizabeth M. Stringer, Bellington Vwalika, David M. Stamilio, and Jeffrey S. A. Stringer "An automated framework for image classification and segmentation of fetal ultrasound images for gestational age estimation", Proc. SPIE 11596, Medical Imaging 2021: Image Processing, 115961N (15 February 2021); https://doi.org/10.1117/12.2582243
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CITATIONS
Cited by 1 scholarly publication and 3 patents.
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KEYWORDS
Ultrasonography

Image classification

Fetus

Image segmentation

Databases

Error analysis

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